Maximizing Operational Optimization Through Application Time-Series KPIs

Key Performance Indicators

The term “KPI” stands for Key Performance Indicator, which is basically a metric revealing how well certain operations are progressing. KPIs can be applied to infrastructure which has nothing to do with IT applications, or they can strictly be applied to digital operations.

As technology like IoT (the Internet of Things) and cloud computing have come to predominate, more solutions in terms of metrics acquisition and management become available. Specific KPIs pertaining to operational infrastructure reveal key components of application performance.

Specifically, time-series KPIs can help you identify issues before they impact operations, and ensure upgrades or other augmentations have been successfully applied. They won’t tell you exactly the cause, but they’ll give you the information you need to help narrow things down. A few examples of KPIs might include Requests Per Minute, Error Rates, and Average Response Time.

Over a specified period, metrics are gathered pertaining to the needs of the user. Certain solutions allow you to choose areas to concentrate metrics collection. Additionally, you can apply a “rules engine” which will alert you when certain trends develop, or should erroneous operations be detected.

Illustrating Application Time-Series KPIs

So for the sake of illustration, imagine you’ve got a number of web service calls which have a specific response time you’re looking to hit. Software which can capture time-series KPIs would be able to show you whether there are operationally impacting abnormalities.

If response time were lagging, or if calls were waning, you’d be able to get a good idea where improvement is necessary. If you suspect an issue, tools of this kind can help you identify it. Though they themselves don’t specify any underlying cause of abnormal operations, they can help you narrow down where such a thing may be coming from. Also, you can use such KPIs to project future targets.

With this information you can also determine whether deviation is allowable or not. You’re going to have ebb and flow that is natural. With KPIs of the time-series type, you can determine where the delineator lies for what may be considered a relevant deviation.

An Infrastructural EKG

It may be normal for performance, requests, and response time to oscillate like a sine wave on an EKG. But if suddenly there’s a spike either direction, relevant KPIs can alert you immediately, and give you a time-frame in which the spike occurred that you can use to determine its approximative cause.

If you did something right, these metrics can help reveal as much. If you did it wrong, they can do the same. Additionally, they can show you where things beyond your control are impacting operations, allowing you to adjust around such exigencies should they develop in the future.

Accordingly, it’s absolutely integral to acquire software which has been designed for this purpose, and is known to be effective. Applying digital infrastructure management solutions to your IT infrastructure lets you monitor directories, audit file-sharing, facilitate permissions analysis, and other key monitoring services which can allow you to run time-series KPIs, as we’ve seen on this great source on quick and easy monitoring of Amazon ELB | Log analysis | log Monitoring by Loggly.

Even the best application will need to be improved over time. When an application is launched, there is an initial phase where users are learning to balance operations around it. For a burgeoning startup who has launched an app their clientele use on, perhaps, an ecommerce platform, this can be a very risky period. If users are encountering frequent difficulties just using the app, it will cut into business.

Application Management Considerations

Generally a beta version of an application is tested before it is released in the mainstream. This allows common errors to be noticed and dealt with. Error logging is key in catching operational problems and correcting them. But error logs don’t happen until the errors transpire.

Meanwhile, KPIs can help predict errors through long-term data collection of the time-series variety. So it’s essential not only to log errors in a visible way, and have protocols for dealing with them, you’ve got to have a conceptually external monitoring solution as well which reveals trends.

Cybercrime Considerations

Something else to consider are market fluctuations and cybercrime. A DDoS ( Distributed Denial of Service) attack bombards a platform like a website, or program like an application, with access requests, ultimately over-powering servers and forcing the program to freeze, glitch out, crash, or become damaged in other ways.

Similar effects transpire when there’s suddenly a spike in user requests owing to a successful marketing campaign, or good PR. Time-series application KPIs can show you where an application is becoming stressed, and where perhaps greater bandwidth may be required, or something similar.

Managing Market Fluctuation

On that note, the market can change on you quickly. If you don’t know where you were, then it’s hard to tell where you’re hemorrhaging funds. You can’t apply a bandage if you don’t know where the injury is.

What makes sense is acquiring time-series application KPIs through monitoring solutions designed for this and other infrastructural management purposes. Establishing such a system of monitoring will help your business operate optimally, while simultaneously assisting you in avoiding operationally hindering phenomena, and helping you predict future trends.